THREE-DIMENSIONAL RECONSTRUCTION OF
MICROSTRUCTURES IN α + β TITANIUM ALLOYS
A Thesis
Presented in Partial Fulfillment of the Requirements for
The Degree Master of Science in the
Graduate School of The Ohio State University
By
Erin P. Barry, B.S.
*****
The Ohio State University
2008
Master’s Examination Committee:
Dr. Hamish L. Fraser, Advisor
Approved by
Dr. Yunzhi Wang
____________________________________
Advisor
Graduate Program in Materials Science and Engineering
ABSTRACT
Titanium and its alloys are comparatively recent “newcomers” to the
metallurgical market. They are gaining widespread acceptance for use in the recreational,
aerospace, biomedical, petro-chemical, and commercial processing industries due to their
combination of unique and advantageous properties, including high strength, low density,
and superior corrosion resistance to most aggressive agents. The material properties of
titanium and its alloys can be optimized and tailored by engineering the microstructure
via control of chemistry, processing route, and heat treatment. The morphology of the
two crystallographic allotropic phases can be manipulated to refine the structure and
produce desirable mechanical property combinations. Microstructural constitution of the
titanium alloys is classified according to the dominant phase within the alloy; alpha +
beta (α + β) titanium alloys are the most widely used alloys. The temperature of the final
heat treatment of the α/β components is governed by the service requirements. In order
to evaluate the behavior of these alloys for future applications, it is imperative that the
microstructural features and characteristics be quantified and examined on a spatial
dimension. The Robo-Met.3D is a high precision robotic serial sectioning device that can
fulfill this need.
Initially, several months were spent resolving problems with the functioning of
the Robo.Met.3D. Two-dimensional (2-D) stereology was done on Timetal 550 using
ii
automated batch processing with Adobe Photoshop and Fovea Pro.
Images from
different locations on the gage were obtained and compared. Final data demonstrated
quantitative differences which were the result of the heat treatment. Discrepancies and
inconsistencies in the data were identified as limiting factors in the reproducibility of the
procedure in future work.
Serial sectioning using focused ion beam (FIB) was performed using Timetal
550, and three-dimensional (3-D) reconstruction was done using IMOD. Robo-Met.3D
procedures and algorithms were identified for serial sectioning collection for titanium
alloys using Ti-6Al-4V.
Recommendations for future work include developing more efficient procedures
for coloring in the microstructural features in the Adobe Photoshop CS™.
A new
procedure is needed to mount and polish the sample to prevent sample curvature due to
the polishing step. Also, the small size of the secondary alpha (α ) presents a challenge
when examining microstructural features; however, it is imperative that these features be
examined in the future to determine their effect on mechanical properties.
iii
Dedicated to my parents, my grandfather, and Mike
. . . for all of their love and support
iv
ACKNOWLEDGEMENTS
First and foremost, I would like to convey my heartfelt gratitude to my advisor,
Dr. Hamish L. Fraser for giving me the opportunity to pursue a higher degree of
education. In addition, Dr. Fraser has been a constant and amazing source of wisdom,
insight, and knowledge.
I will always be indebted to Dr. Peter Collins for his invaluable intellectual
support, technical expertise, and untiring effort in helping me with my work.
His
guidance and advice were instrumental in enhancing my understanding and assisting with
the compilation of my thesis.
In addition, I would like to thank the members of Dr. Fraser’s undergraduate and
graduate research groups for their friendship and assistance. I feel very fortunate to have
been given the opportunity to work with such an extraordinary group of people.
I would like to acknowledge my grandfather, Robert Lasky, who stimulated and
supported my desire to become an engineer. And lastly, I would like to thank my family
and Mike for their continuing encouragement and reassurance during my endeavor.
Thank you!
“All men by nature desire knowledge.”
~Aristotle
v
VITA
1982……………………………………Born to John and Laura Barry,
Mount Holly, New Jersey
2000……………………………………High School Diploma, Lenape Regional
High School, Medford, New Jersey
2005……………………………………B.S. Materials Science and Engineering,
The Ohio State University, Columbus, Ohio
FIELDS OF STUDY
Major Field: Materials Science and Engineering
vi
TABLE OF CONTENTS
ABSTRACT........................................................................................................................II
ACKNOWLEDGEMENTS............................................................................................... V
VITA ................................................................................................................................. VI
FIELDS OF STUDY......................................................................................................... VI
LIST OF FIGURES ........................................................................................................... X
LIST OF TABLES......................................................................................................... XIII
CHAPTER 1 ....................................................................................................................... 1
CHAPTER 2 ....................................................................................................................... 3
2.1 History of Titanium....................................................................................................... 3
2.2 Applications and Properties of Titanium and Titanium Alloys .................................... 4
2.2.1 Acquisition and Production Costs.......................................................................... 4
2.2.2 Properties of Titanium and Titanium Alloys ........................................................ 4
2.2.3 Usage...................................................................................................................... 6
2.2.4 Alloy Specifications.............................................................................................. 8
2.3 Primary Crystallographic Allotropic Phases............................................................... 10
2.3.1 Transformation Temperature ............................................................................... 10
2.3.2 Substitutional Solutes and Interstitial Solutes...................................................... 11
2.3.3 Stabilization of Phases ......................................................................................... 12
2.3.3.1 Alpha Stabilizing Elements........................................................................... 13
2.3.3.2 Beta Stabilizing Elements ............................................................................. 13
2.3.3.2.1 Isomorphous β Stablizing Elements...................................................... 13
2.3.3.2.2 Eutectoid β Stabilizing Elements .......................................................... 14
2.4 Alloy Classification .................................................................................................... 15
2.4.1 Alpha Alloys ........................................................................................................ 16
vii
2.4.1.1 Commercially Pure Titanium........................................................................ 17
2.4.1.2 Near α Alloys ................................................................................................ 18
2.4.2 Beta Alloys........................................................................................................... 18
2.4.3 Alpha and Beta Alloys ......................................................................................... 19
2.5 Physical Properties of Titanium.................................................................................. 19
2.6 Titanium Microstructure: Ti-6Al-4V......................................................................... 20
2.6.1 Aluminum Alloying Element............................................................................... 20
2.6.2 Vanadium Alloying Element .............................................................................. 21
2.7 Microstructure Evolution ........................................................................................... 21
2.7.1 Martensitic Transformation ................................................................................. 22
2.7.2. Sympathetic Nucleation/Nucleation and Growth ............................................... 24
2.7.2.1 Lamellar Microstructure ............................................................................... 26
2.7.2.2 Lamellar Properties....................................................................................... 27
2.7.3 Bi-Modal (α + β) Processing............................................................................... 30
2.7.3.1 Bi-Modal Microstructure .............................................................................. 33
2.7.3.2 Alloy partitioning effect................................................................................ 34
2.8 Timetal 550 ................................................................................................................. 35
2.9 Stereology ................................................................................................................... 35
2.10 Serial Sectioning for 3-D Analysis ........................................................................... 36
2.11 Robo-Met.3D ............................................................................................................ 39
CHAPTER 3 ..................................................................................................................... 45
3.1 Heat Treatment............................................................................................................ 45
3.2 Sample Preparation and Microscopy .......................................................................... 49
3.3 Stereology Set up ........................................................................................................ 49
3.4 Characterization .......................................................................................................... 50
3.4.1 Thresholding α Laths ........................................................................................... 50
3.4.2 Volume Fraction α and Lath Thickness............................................................... 52
3.5 Serial Sectioning for 3D Microstructures .................................................................. 53
3.6 FIB .............................................................................................................................. 55
CHAPTER 4 ..................................................................................................................... 63
viii
4.1 Stereology Results ...................................................................................................... 63
4.2 Robo-Met.3D Results ................................................................................................. 69
4.3 FIB Results................................................................................................................. 76
CHAPTER 5 ..................................................................................................................... 80
5.1 Summary .................................................................................................................... 80
5.2 Future Work ............................................................................................................... 81
REFERENCES ................................................................................................................. 83
ix
LIST OF FIGURES
Figure 2.1 Titanium usage in a GE-90 aero-engine......................................................... 7
Figure 2.2 General characteristics and typical applications of titanium alloys ............... 8
Figure 2.3 Unit cell of α phase (A) Unit cell of β phase (B) ......................................... 11
Figure 2.4 Interstitial (A) and Substitutional (B) Elements........................................... 12
Figure 2.5 Alloying effects on titanium phase diagram................................................. 15
Figure 2.6 Ti-6Al-4V quenched from the β phase field (A) OM (B)TEM................... 23
Figure 2.7 Schematic diagram of thermomechanical processing for lamellar structures
in α + β titanium alloys ..................................................................................................... 25
Figure 2.8 Schematic representation of the crystallographic relationship between the α
plates and β matrix in the α colonies................................................................................. 26
Figure 2.9 Schematic representation of α + β titanium alloys ....................................... 27
Figure 2.10 Important processing parameters, final microstructural features and their
influences on mechanical properties for lamellar structures............................................. 28
Figure 2.11 Lamellar α + β microstructure in Ti-6Al-4V slowly cooled from the β phase
field (a) OM (b) TEM ....................................................................................................... 29
Figure 2.12 Lamellar structure with different cooling rates. A: 1 oC/min,
B: 100 oC/ min, C: 8000 oC/min [21].............................................................................. 29
Figure 2.13 Thermo-mechanical processing for bi-modal microstructures in α + β
titanium ............................................................................................................................. 32
Figure 2.14 Bimodal microstructure of titanium at different cooling rates ................... 32
Figure 2.15 Important processing parameters, final microstructural features, and their
influence on mechanical properties .................................................................................. 34
Figure 2.16 Cross sections are used to construct a 3-D shape ....................................... 38
x
Figure 2.16 Robo-Met.3D system with robotic arm, automatic polisher, etching station,
and microscope ................................................................................................................. 40
Figure 3.1 Timetal 550 B01 Sirion SEM image (A) and thresholded (B)..................... 51
Figure 3.2 Schematic drawing of the 3 types of mountings used for the Robo-Met.3D
system. (A): Epoxy stub (B): Titanium stub with spot welded smaple (C): Titanium
stub with embedded sample .............................................................................................. 54
Figure 3.3 Robo-Met.3D serial section image #70 before (A) and after (B) α globs were
colored............................................................................................................................... 57
Figure 3.4 Ti-6Al-4V image taken with the NOVA FIB............................................... 58
Figure 3.5 Serial Sections of Ti-6Al-4V layers created with the NOVA FIB............... 59
Figure 3.6 3-D reconstruction of Ti-6Al-4V α laths from serial sections taken with the
NOVA FIB shown at different angles (A) and (B)........................................................... 60
Figure 3.7
Serial sectioning images from the FIB of Timetal 550 showing the
appearance of α laths in the center of the grain ................................................................ 61
Figure 3.8 3-D reconstruction of Ti-6Al-4V α laths from serial sections taken with the
NOVA FIB (A) and (B) .................................................................................................... 62
Figure 4.1
B08 Images taken at different locations along the gage of a Timetal 550
specimen. A) Center of gage. B) Away from center of gage.......................................... 65
Figure 4.2 Amount of material removed versus Time at 20 RPM for the Multiprep on
the Robo-Met.3D system .................................................................................................. 70
Figure 4.3 Amount of material removed versus Time at 50 RPM for the Multiprep on
the Robo-Met.3D system .................................................................................................. 70
Figure 4.4 Robo-Met.3D images A) Ti-6Al-4V image number 40 B) Ti-6Al-4V image
number 50 ......................................................................................................................... 74
Figure 4.5 Ti-6Al-4V chart showing the variation in area fraction of alpha in each serial
section Robo-Met.3D image ............................................................................................. 75
Figure 4.6 FIB serial section of Timetal 550 showing possible sympathetic nucleation
........................................................................................................................................... 79
xi
Figure 4.7
3-D α laths of Timetal 550 created in IMOD……………………………...80
Figure 4.8 Grain boundary α allotriomorphs in 2-D (a) and 3-D (b,c)…………………81
xii
LIST OF TABLES
Table 2.1 Titanium alloy properties compared to Fe, Ni, and Al .................................... 5
Table 2.2 ASTM grades and applications of the most popular titanium alloys............... 9
Table 2.3 Chemical compositions of the ASTM grades of titanium alloys..................... 9
Table 2.4 Alloying elements: Range and effect on structure........................................ 15
Table 2.5 Chemical composition and physical properties of Timetal 550 .................... 35
Table 2.6 Comparison of steps for creating serial sections manually and with the RoboMet.3D .............................................................................................................................. 41
Table 2.7 Influence of microstructural parameters on mechanical properties of α + β
Ti-alloys and underaged Al-alloys.................................................................................... 43
Table 3.1 Gleeble ® heat treated A samples.................................................................. 46
Table 4.1 α lath data obtained from the Gleeble 3800 ® heat treated samples. Column A
data was taken from the center of the gage and column B data was obtained from samples
taken away from the center of the gage ............................................................................ 66
Table 4.2 Average volume fraction of globular α.......................................................... 72
Table 4.3 Space between the α laths from figure 4.7…………………………………..80
Table 4.4 α lath thickness from figure 4.7……………………………………………..80
Table 5.1 Current and projected capabilities of Robo-Met.3D...................................... 85
xiii
CHAPTER 1
INTRODUCTION
The high acquisition and processing costs of titanium previously limited its
widespread use. However, as promising technology emerges to lower these costs,
titanium is steadily gaining popularity as a material of choice for diverse structural
applications. Research to understand the microstructure of titanium is crucial to
designing and maximizing its mechanical properties for service applications.
Innovative technology, such as the Robo-Met.3D, provides a method to generate
three-dimensional (3-D) images of microstructures of titanium alloys. However,
procedural steps for using the Robo.Met.3D on these alloys have not been previously
described.
This thesis is organized into four separate chapters. Chapter two provides a
background and literature review. This includes an overview of titanium: its history
and usage for commercial, industrial, aerospace, medical, and consumer applications.
Chapter two also reviews titanium alloying additives, allotropic crystallographic
structures, phase transformation, Timetal 550, stereology, and 3-D serial sectioning.
1
Chapter three discusses research undertaken and completed for compilation of
this thesis. A brief description of the equipment and technology used is provided.
Procedures and methodology are described in detail.
Chapter four discusses the results and conclusions, and chapter five
summarizes the work completed and makes recommendations for future work and
research.
2
CHAPTER 2
BACKGROUND AND LITERATURE REVIEW
2.1 History of Titanium
In 1791, William Gregor, an amateur mineralogist, initially discovered titanium
in dark, magnetic iron sand (ilmenite). In 1795, Klaproth, a German scientist,
identified an oxide of an unknown element, which was subsequently determined to be
the same as discovered earlier by Gregor. The metal was bestowed with the name
“titanium” in reference to the titans of Greek mythology, who symbolized power and
strength. However, titanium was rarely used up until about 1950, at which time the
Kroll process was commercialized to make the metal more readily recoverable from
the ores [1-4].
Titanium is the fourth most plentiful metal and ninth most abundant element
found within the Earth’s crust. Titanium occurs naturally as an oxide, TiO2 (rutile) or
as a mixed oxide with iron, FeTiO3 (ilmenite). Leucoxene is a commercial mineral
that is an alteration product of ilmenite [1-5].
3
2.2 Applications and Properties of Titanium and Titanium Alloys
2.2.1 Acquisition and Production Costs
When compared to other alloys, titanium alloys are regarded as expensive;
however, the combination of their unique and useful properties provides justification
for the higher initial cost.
Durability and decreased maintenance demands over
lifetime and longer service life offset the higher price to make titanium and its alloys
cost effective [3, 4, 6]. The overall higher cost of titanium is associated with multiple
factors, including energy expenses and the initial expenditures associated with
acquisition, extraction, and forming. In addition, titanium is highly reactive with
oxygen; therefore, gas shielding in an inert atmosphere is required during the
production process to prevent oxygen ingress into the metal and alloys [4, 6, 7].
2.2.2 Properties of Titanium and Titanium Alloys
Titanium is used today for its reliability afforded through its structural
efficiency and corrosion resistance to different media. Its structural efficiency is the
result of a combination of its high strength and low density properties [1, 2]. Titanium
has strong passivation tendencies which impart resistance and immunity to corrosion
from most mineral acids, chlorides, and oxidizing agents. Titanium is available in all
mill product forms, including P/M products, castings, wrought plate, sheet, tube, bar
and wire forms. Some alloys are precisely tailored to obtain optimal combinations of
properties to meet specific needs and intended end use applications [6].
4
By altering the alloy chemistry and processing parameters/heat treatment, the
titanium alloys can be designed to obtain an ideal combination of property
requirements for the intended service application [1]. However, in general, all
properties cannot be simultaneously maximized.
For example, fracture-critical
structures function more efficiently when made from materials that are processed to
optimize high fracture toughness. However, fatigue limited structures have a higher
sensitivity to crack initiation and crack growth rate [8]. Table 2.1 shows titanium
alloy properties compared to iron (Fe), nickel (Ni), and aluminum (Al) [4].
Table 2.1 Titanium alloy properties compared to Fe, Ni, and Al [4]
Titanium exhibits resistance to steam up to temperatures of 600° F (or 315°C)
and pressures as high as 2000 psi [3]. Titanium and its alloys have optimal heattransfer properties, low density, and a fairly high melting point [6]. Titanium’s higher
melting temperature makes it the material of choice over aluminum for use in
structural applications with temperatures above 150° C [4].
5
Titanium has high reactivity with oxygen; when exposed to air, it forms a
adherent oxidized surface layer which provides superior corrosion resistance in
hostile and aggressive operating environments.
Alloying elements influence the
corrosion resistance because they can affect the composition of the protective oxide
film [3, 4, 6]. This coherent film, which is typically rutile (TiO2), forms immediately
upon exposure of a fresh surface to air or moisture. Titanium has a strong affinity for
oxygen; therefore, it is has the capability to regenerate or repair a damaged film in
environments where there is just a small amount of moisture or oxygen present.
Damaged or ruptured oxidized films will not self-heal in an anhydrous (nonoxygen)
environment, which makes them susceptible to crevice corrosion [3, 6, 9].
2.2.3 Usage
Due to their excellent corrosion resistance, high strength to weight ratio, easy
formability, and fatigue toughness, titanium and its alloys are attractive to structural
designers for use as primary components in the high performance aerospace, military,
and petrochemical industries [1, 4, 6, 7]. Figure 2.1 displays titanium usage for the
components within a GE-90 aero-engine [4].
Due to their biocompatibility, titanium and its alloys are used extensively in the
manufacture of biomaterials for joint replacement, fracture fixation, dental implants
and interventional cardiovascular devices.
Titanium-based medical devices are
nontoxic, can withstand exposure to human body fluids, and can resist degradation by
most mineral acids and chlorides [6, 10].
6
Figure 2.1 Titanium usage in a GE-90 aero-engine [4]
Titanium is also used commercially in the manufacture of recreational and
consumer products, including golf clubs, costume jewelry, tennis rackets, bicycle
frames, running shoe spikes, etc.
Commercially pure (CP) titanium is used to
produce heat exchangers, condensers, and storage tanks [1, 2, 6].
Figure 2.2 shows the general characteristics and typical applications of titanium
alloys [1].
7
Figure 2.2 General characteristics and typical applications of titanium alloys [1]
2.2.4 Alloy Specifications
The chemical composition of unalloyed titanium and its alloys are governed
by specifications and requirements set forth by an international standards developing
organization, the American Standards for Testing and Materials (ASTM) [3]. The
ASTM grades and applications for the most popular titanium alloys are noted in table
2.2 [1].
Table 2.3 displays the chemical compositions of the ASTM grades of
titanium alloys [3].
8
Table 2.2 ASTM grades and applications of the most popular titanium alloys [1]
Table 2.3 Chemical compositions of the ASTM grades of titanium alloys [3]
9
2.3 Primary Crystallographic Allotropic Phases
Titanium is an allotropic element; it can occur in more than one crystalline
state. Titanium microstructures are almost completely dependent on the size, shape,
and distribution of two primary crystallographic phases: alpha (α) is a hexagonal
close packed structure (hcp) and beta (β) is a body center cubic structure (bcc) [1, 4,
8,10-12].
2.3.1 Transformation Temperature
The alpha to beta (α→β) transformation temperature or beta (β) transus
temperature is the primary “key” to the processing and evolution of microstructures in
titanium alloys. The β transus temperature is a critical parameter because processing
and heat treatment routes are carried out with reference to some point above or below
the β transus [4-6]. The β transus temperature separates the single phase β field from
the dual phase α + β field. The specific temperature is dependent on alloy chemistry
[1, 13, 14]. The β transus is defined as “the lowest equilibrium temperature at which
the material is 100% beta” [5]. The β transus temperature is the transformation
temperature from α + β or α to all β [5].
The hcp crystal structure, or α phase, in titanium exists at room temperature
and is stable below the allotropic phase transformation temperature of 882° C. A
transformation to the bcc crystal, or β phase, occurs when titanium is heated to
temperatures above 882° C. It is then stable until its melting point of 1668° C [1, 4,
7, 9, 10].
10
Phase transformations can be described as an: “extensive rearrangement of
atomic or molecular structure with or without an accompanying change in chemical
composition” [15]. Figure 2.3 shows a schematic drawing of the unit cells of the two
phases [4].
Figure 2.3 Unit cell of α phase (A) Unit cell of β phase (B) [4]
2.3.2 Substitutional Solutes and Interstitial Solutes
The exact temperature for transformation between the two phases is
influenced by the metal’s purity. Based on this principle, the alloying elements for
titanium can be separated into two categories: substitutional solutes and interstitial
solutes. Substitutional elements, such as molybdenum (Mo) and vanadium (V), serve
as a substitute for titanium on lattice sites. Interstitial elements, such as oxygen (O),
nitrogen (N), and hydrogen (H), “squeeze in” and fill in the spaces between the parent
atoms [4, 16]. Oxygen, nitrogen, and carbon are carefully controlled to improve
11
ductility and fracture toughness for cryogenic service applications.
Alloys with
controlled interstitial content are referred to as ELI or extra low interstitial [5].
The structural differences between interstitial and substitutional formation within
metal material are indicated in figure 2.4 [16].
Figure 2.4 Interstitial (A) and Substitutional (B) Elements [16]
2.3.3 Stabilization of Phases
The selection of alloying elements is influenced by the ability of the element
to stabilize the α or β phase, or increase or decrease the β transus temperature. Either
crystal structure can be stabilized at room temperature by alloying titanium with other
elements [4, 12]. Additive alloying elements can be collectively classified as either α
or β stabilizers depending on whether or not they stabilize the hcp phase or the bcc
phase. Some elements do not specifically stabilize either the α or β phase; zirconium
is an α and β strengthener [1, 4, 5].
12
2.3.3.1 Alpha Stabilizing Elements
The elements Al, O, N, and C are strong α stabilizing elements; they raise the
β transus temperature with increasing solute content.
Aluminum is the most
frequently used element constituent in titanium alloys; it is the only common metal
that can raise the transition temperature and exhibit a significant solid solubility in the
α phase for two phase microstructures. Oxygen is classified as an alloying element in
titanium in applications where oxygen is introduced to get a desired strength level.
Boron (B), gallium (Ga), germanium (Ge) and the rare earth elements are also α
stabilizers. However, their solid solubilities are lower than that of aluminum or
oxygen; hence, they are very rarely used as an alloy [4].
2.3.3.2 Beta Stabilizing Elements
In β alloys, adding 30% of β stabilizing elements, such as V, Mo, Fe, and Ni,
will stabilize the β phase at room temperature [1]. There are two types of β stabilizing
elements that lower the transus temperature: β isomorphous and β eutectoid forming
[1].
2.3.3.2.1
Isomorphous β Stablizing Elements
The most commonly used and preferred isomorphous β stabilizing elements in
titanium alloys are V, Mo, and niobium (Nb); sufficient concentrations of these
elements enable the β phase to be stabilized to room temperature. Tantalum (Ta) and
rhenium (Re) also belong to this group, but they are limited in usage due to density
factors [1, 2, 4].
The isomorphous stabilizers continuously lower the β transus
13
temperature [17].
Some β isomorphous stabilizing elements, such as iron and
manganese, are preferred alloying additions to enhance hardenability and improve
heat treatment response [12, 5].
2.3.3.2.2
Eutectoid β Stabilizing Elements
The eutectoid β stabilizing elements exhibit low solubility in α titanium [5].
They act to lower the β transus temperature until this process is interrupted by
compound formation [17]. The β eutectoid stabilizing elements that are most
commonly used in titanium alloys are iron (Fe), chromium (Cr), and silicon (Si).
Certain elements, including nickel (Ni), copper (Cu), manganese (Mn), tungsten (W),
palladium (Pd), and bismuth (Bi), are used only for one or two dedicated functional
purposes. Other β eutectoid forming elements, such as cobalt (Co), silver (Ag), gold
(Au), platinum (Pt), beryllium (Be), lead (Pb), and uranium (U), are not used as
alloying elements in titanium [4]. The maximum solubility in β titanium decreases
and eutectoid temperature increases with an increase in group number [1]. The β
eutectoid alloying elements form intermetallic compounds whereas the β
isomorphous elements do not [5, 12].
Phase diagrams of the effects of alloying elements on the titanium can be
found in figure 2.5 [4]. Alloying elements with range and effect on structure are in
table 2.4 [5].
14
Figure 2.5 Alloying effects on titanium phase diagram [4]
Table 2.4 Alloying elements: Range and effect on structure [5]
2.4 Alloy Classification
The two crystal structures, hcp and bcc, are the foundation for identifying the
classes of titanium alloys [4, 12]. The dominant phase of the alloy determines the
classification [6]. The three basic classifications for purposes of this thesis are α
phase alloys, β phase alloys, and α + β phase alloys. Alpha alloys are primarily α, but
15
they may contain a small fraction of β. Both phases are present within α + β alloys
[1, 4, 6]. Other classification systems identify additional categories for titanium
phase diagrams, such as commercially pure/modified titanium [3, 13], near α alloys
[1, 9], advanced titanium alloys, including titanium-matrix composites [13], titanium
aluminides [1,12,13], and metastable β alloys [1, 5].
Thermo-mechanical
processing
of
these
alloys
affects
both
their
microstructures and mechanical properties; this is done mainly by controlling the
hexagonal close packed (hcp) α phase within the matrix of the body centered cubic
(bcc) β phase. Different alloying chemistries produce divergent microstructures; this
in turn influences mechanical properties [1, 12]. Once the alloying elements are
selected,
the
resultant
mechanical
properties
can
be
optimized
by
deformation/working to control the size, shape, and dispersion of the dual phases
[12]. The primary purpose of heat treatment is to “change a starting microstructure
formed during the manufacturing route into a microstructure that has an appropriate
balance of properties for a given application” [14].
2.4.1 Alpha Alloys
Alpha alloys are single phase and therefore, cannot be heat treated to
manipulate the microstructure to develop high mechanical properties [1, 5, 13]. The
properties of these alloys are more dependent on composition when compared to the
α + β and β alloys. They are “simpler,” and they contain sufficiently small total alloy
additives. The α titanium alloys have medium strength, relatively good toughness
16
and creep resistance. There are relatively few mechanisms available to strengthen α
alloys, and the extent of their usage is limited by practicality [4].
These alloys can be strengthened by grain size strengthening, texture
strengthening, precipitation hardening by α2 phase formation, and solid solution
strengthening by interstitial and substitutional elements [4, 17] Alpha alloys are used
in applications where corrosion resistance and weldability are desired properties [4]
Alpha alloys do not have ductile-brittle transformation, so they are suitable for use in
cryogenic applications [17].
2.4.1.1 Commercially Pure Titanium
Commercial titanium (CP) or unalloyed titanium is classified as an α alloy; it
exists in an all α phase at room temperature [1]. CP titanium is available in several
ASTM grades, which are differentiated by varying amounts of trace elements,
including carbon, hydrogen, iron, nitrogen, and oxygen. CP titanium is used in the
aerospace industry where the application requires material that is more heat resistant
than aluminum and lighter than steel [11]. CP titanium is usually forged, hot rolled,
and heat treated in the α phase field [1].
Adding alloying elements to pure titanium yields alloys that can be heat
treated or processed in a range where the alloy is dual phase [5]. CP titanium alloys
differ by the amount of oxygen and iron that is present within each alloy. Alloys with
higher interstitial content have higher strength, hardness and transformation
temperature when compared to those that are high-purity [12].
17
2.4.1.2 Near α Alloys
As mentioned earlier, some classification systems include near α alloys as an
entirely separate category. Briefly, these alloys contain a small amount of β
stabilizing elements (1 to 2 wt. %) that retain some β to provide supplemental
microstructure and property control. However, they act more like α alloys than α + β
alloys. They improve strength and workability, and provide a balance between the
creep resistance of the simple α alloys and the high strength properties of the α + β
alloys [1, 6, 13].
2.4.2 Beta Alloys
The β alloys are “metastable”; they can transform to a “balance of structures”
[5]. Beta alloys can be heat treated to a variety of strength levels. They can be
customized to maximize ideal strength-toughness combinations for given
applications: moderate strength with high toughness or high strength with moderate
toughness can be developed [18]. Beta alloys also offer high strength where yield
strength is more important than creep strength [6].
The β alloys exhibit excellent forgeability and cold working capabilities [13].
Beta alloys are susceptible to ductile-brittle transformation; therefore they are not
appropriate for cryogenic applications [10]. These alloys are used in specialized
service applications that require burn resistance and corrosion resistance [1]. They
exhibit better fracture toughness than the α + β alloys [6].
18
2.4.3 Alpha and Beta Alloys
The α + β titanium alloys contain metallurgically balanced α and β stabilizing
elements with 4 to 6% of beta stabilizers [1]. These alloys are used in applications
that require optimal levels of competing characteristics. This includes balancing
propitious properties such as high tensile strength vs. fracture toughness or good
creep resistance vs. low cycle fatigue or high tensile strength vs. high cycle fatigue
[10]. The microstructure and properties of these alloys can vary significantly based
on heat treatment and thermo-mechanical processing [1]. In order to produce the
desired mechanical properties in the end product, careful consideration is given in
selecting and balancing alloy composition, solution temperature, and aging conditions
[13]. These alloys can be hardened through heat treatment, and solution treatment
plus aging are used to maximize strength [5].
2.5 Physical Properties of Titanium
Titanium is a transition element with an atomic number of 22 and atomic
weight of 47.90. Titanium’s position in the periodic table gives it unique physical and
electronic properties which make it a suitable material to produce a broad spectrum of
alloys [1, 7]. Due to its two allotropic forms, the alloying behavior of titanium from
an electronic standpoint is complex. When compared to the α phase, the density of the
β phase is slightly greater, which suggests that the interatomic bonds are dependent
on the local electronic environment [7].
19
2.6 Titanium Microstructure: Ti-6Al-4V
To describe the titanium microstructure, the α + β titanium alloy Ti-6Al-4V
will be used since it is among the most widely used titanium alloys in the world. This
versatile alloy accounts for approximately 45% of the total titanium production [13].
Ti-6Al-4V was first introduced in 1954 and is considered to be a “general purpose
titanium alloy” or “workhorse of the industry”. Ti-6Al-4V is an alpha-rich alpha-beta
alloy and is produced in all mill product forms along with the casting and powder
forms [11]. In addition to being lightweight, this alloy possesses high strength along
with excellent corrosion resistance, stiffness and fracture-critical toughness. These
properties make it an attractive and feasible choice for aerospace and military
applications [5].
Ti-6Al-4V is usually used for applications with temperatures from -350° F to
750° F (-210° C to 400° C. The density of Ti-6Al-4V is 0.16 lb/in.3, which is 56% of
that of steel. The melting point ranges from 2965° F--3000° F (1630° C--1650° C)
[11].
2.6.1 Aluminum Alloying Element
Ti-6Al-4V alloy is 6% aluminum, which stabilizes the α phase and 4%
vanadium, which stabilizes the β phase [2]. The addition of aluminum increases the
allotropic transformation temperature of titanium. The 6% content is sufficient to
strengthen the α phase by solid solution, but yet, it is not so high as to cause
embrittlement [4, 7].
20
2.6.2 Vanadium Alloying Element
Vanadium is a β phase stabilizing additive that solid-solution strengthens the β
phase to refine the microstructure and strengthen the alloy [4, 7,11]. It is believed
that the β→α phase transformation is primarily controlled by diffusional
redistribution of vanadium between the two phases. The α plates formed at slower
cooling rates are thicker than those obtained at faster cooling rates due to longer
periods of diffusion [19].
Katzarov, Malinov, and Sha [19] developed a predictive mathematical model
and computer program for the numerical simulation of the nucleation and growth
processes of the α plates during β→α transformation in the Ti-6Al-4V alloy.
Katazrov et al. described a numerical procedure that used vanadium concentration
and temperature as variables in random nucleation.
Using computer program
packages, they simulated the effects of different heat treatments on the morphology of
microstructural evolution. Their detailed findings are beyond the scope of this thesis,
but their model can be used to predict the morphology of the actual application of the
β→α phase transformation in Ti-6Al-4V.
2.7 Microstructure Evolution
There are many theories and experimental studies that have attempted to
understand, characterize and model the phase transformation process.
Various
authors have attempted to establish a fundamental understanding of these
controversial and complex mechanisms.
21
According to Lutjering [4], depending on cooling rate and alloy composition,
the transformation of the β phase (bcc) to the α phase (hcp) can occur by diffusion
controlled nucleation and growth or a martensitic process [4]. Titanium alloys are in
single-phase β when they are heat treated above the β transus temperature. The
specific temperature is dependent on the alloy chemistry. On cooling, through the β
transus temperature, β can undergo transformation to different equilibrium or
nonequilibrium phases [1].
The rate of cooling, or quenching in water, oil or other suitable medium, is
critical for distinguishing between the two modes of transformation: martensitic or
nucleation and growth [1, 8, 11, 13]. Another process, through-transus processing,
has narrow processing windows and is difficult to control. Its use within industrial
applications is questionable [20].
Depending on cooling rate and heat treatment, Ti-6Al-4V can form different
microstructures: martensite, colony, Widmanstätten, (basketweave), and globular α
bi-modal.
In addition, mechanical properties of fully lamellar structures can be
improved by generating a “bi-lamellar structure.” An intermediate annealing step is
introduced into the processing route for lamellar structures; this transforms the soft
single phase β lamellae to hard lamella with fine α platelets or laths [21].
2.7.1 Martensitic Transformation
During rapid cooling, such as water or oil quenching, the β phase can
transform to martensite. Rapid cooling eliminates transformation to the α phase [1, 8].
Martensite transformation is described as “diffusionless,” “displacive,” and “shear22
like” [15]. Martensite transformation involves the movement of atoms via a shear
type reaction which produces homogeneous transformation of the bcc into the hcp
lattice over a defined volume. The transformed volume appears plate shaped or disk
shaped for the majority of titanium alloys [4].
The martensitic structure can take one of two forms: α’ (alpha prime) is a
hexagonal crystallographic structure whereas α” (alpha double prime) is an
orthorhombic crystallographic structure. On subsequent aging, these martensitic
structures will decompose to precipitate fine β, which gives useful increments in
strength [1, 5, 6]. The type and amount of α’ or α” that forms with quenching is
dependent on the chemistry of the β phase prior to quenching. Those alloys with
increasing β stabilizing elements have a higher tendency to form α” instead of α’ [1].
Figure 2.6 shows Ti-6Al-4V martensite quenched from the β phase field [4].
A
B
Figure 2.6 Ti-6Al-4V quenched from the β phase field (A) Optical microscopy (OM)
(B)Transmission electron microscopy (TEM) [4]
23
2.7.2. Sympathetic Nucleation/Nucleation and Growth
According to Menon and Aaronson [22] sympathetic nucleation is “the
nucleation of a precipitate crystal, the composition of which differs from that of the
matrix, at the interphase boundary of another crystal of the same phase.” There are
two primary components to the recrystallization step:
the nucleation phase and
growth of new grains. Recrystallization is “the formation of a new grain structure in
a deformed material by the formation and migration of high angle grain boundaries
driven by the stored energy of deformation” [23].
As noted in the schematic phase transformation diagram in figure 2.7, during
recrystallization, the microstructure of the alloy after treatment in the β phase field is
strongly influenced by the cooling rate from the β region. When the alloy is cooled
slowly below the β transus temperature from the β phase field into the α + β phase
field, the α phase initially will preferentially nucleate and form a continuous α layer
along the β grain boundaries. The resulting lamellar structure, which is referred to as
β processed, is “platelike” [4, 19].
As cooling continues, the α plates will nucleate at one of two locations: the
interface of the continuous α layer or along the β grain boundary.
They will grow
and extend into the β grain interior as parallel plates belonging to the same
variant/morphology as the α colony. They continue to grow into the β grain interior
until they meet other α colonies (of a different variant) that had previously nucleated
at other grain boundary locations on the β grain.
sympathetic nucleation [4].
24
This process is known as
The retained β matrix remains as a thin layer separating the individual plates
within the α colonies [4]. Eventually, colonies that underwent nucleation at the β
grain boundaries can no longer fill the entire interior of the grain so they start to
nucleate on the boundaries of other colonies. The overall elastic strain is minimized;
the new α plates nucleate and grow in a nearly perpendicular orientation to the
existing plane. This selective mechanism combined with the smaller α plates within
the colonies leads to a basketweave or Widmanstätten structure [4, 19]. A schematic
representation of the crystallographic relationship between the α plates and β matrix
in the α colonies is shown in figure 2.8 [4].
Figure 2.7 Schematic diagram of thermomechanical processing for lamellar
structures in α + β titanium alloys [4]
25
Figure 2.8 Schematic representation of the crystallographic relationship between the
α plates and β matrix in the α colonies [4]
In his doctoral dissertation, Kar [17] proposed that the basketweave structure
forms through “shooting” of a few α laths into the grain interior from different
colonies growing on different locations on the prior β grain boundary.
The
intersection of these laths gives rise to the basketweave appearance. As the colony
continues to grow, progressively fewer laths continue to grow in the interior while
others stop growing due to intersecting of laths of other variants from nearby
colonies.
2.7.2.1 Lamellar Microstructure
The α and β plates formed during this transformation process are sometimes
called “lamella” and the resultant microstructure is referred to as “lamellar’ [4]. These
plate-like precipitates are also called α laths. The regions of identically oriented laths
are called colonies or clusters or groups of laths that belong to the same
crystallographic variant. A group of colonies can combine to form grains. The α laths
can form two different types of microstructures: colonies of 5 or more α laths with
26
the same orientation, or a basketweave (Widmanstätten) structure whereby the laths
have different origins and cross over each other forming a weave-type structure, or a
“clustering of multiple variants” [17, 24].
Figure 2.9
shows a schematic
representation of α + β titanium alloys [28].
Figure 2.9 Schematic representation of α + β titanium alloys [28]
Some authors consider both the colony and basketweave to be forms of
Widmanstätten morphology [1]. However, others note that the basketweave and
Widmanstätten are the exact same microstructure, and the colony is described as a
distinctly separate entity [25]. The latter distinction will be adhered to within this
thesis.
Other authors [6] refer to the resulting morphology using different
terminology: coarse acicular structures or fine acicular structures.
2.7.2.2 Lamellar Properties
Lutjering [4, 26] notes that the primary features of fully lamellar
microstructures in α + β alloys are the presence of continuous α layers at β grain
27
boundaries, the α colony size, and the size of the individual α lamellae. The α colony,
which may determine effective slip length, is the most influential microstructure
parameter in lamellar microstructures; the cooling rate from the β heat treatment
temperature controls the α colony size.
Important processing parameters, final
microstructural features and their influences on mechanical properties for lamellar
structure are shown in figure 2.10 [21].
Figure 2.10 Important processing parameters, final microstructural features and their
influences on mechanical properties for lamellar structures [21]
A larger α colony size improves macro crack propagation resistance and
fracture toughness [21]. Fine α laths and a basketweave, or Widmanstätten structure,
produce an increase in yield stress. The morphology can be changed from a colony of
similarly aligned α laths to a basketweave by raising the cooling rate or altering the
alloy composition [1, 4].
28
The cooling rate controls the coarseness of the transformed structure. The
lamellar structure becomes finer with an increase in cooling rate. With an increase in
cooling rate, the α colony is decreased with a corresponding reduction in effective
slip length and comparable increase in yield stress. Decreasing cooling rates promote
the formation of a coarse transformed structure. The α plates become very coarse with
very slow cooling [1, 4, 6, 11, 21]. The α phase slowly thickens perpendicular to the
plane; growth is faster along the plane. Hence, the α plates develop [17]. Figure 2.11
shows lamellar α + β microstructure in Ti-6Al-4V slowly cooled from the β phase
field [4]. Figure 2.12 shows the lamellar structure with different cooling rates [21].
Figure 2.11 Lamellar α + β microstructure in Ti-6Al-4V slowly cooled from the β
phase field (a) OM (b) TEM [4]
A.
B.
C.
Figure 2.12 Lamellar structure with different cooling rates. A: 1 oC/min,
B: 100 oC/ min, C: 8000 oC/min [21]
29
Lamellar microstructures have high fracture strength and superior resistance
to creep and fatigue-crack growth. Finer microstructures slow crack nucleation and
exhibit increased strength and ductility. Coarse microstructures are more resistant to
fatigue-crack growth and creep [1, 14].
In alloys with higher concentrations of β stabilizing elements, competition can
develop between the nucleation of α at prior β grain boundaries and the grain interior.
This can cause the formation of a continuous or semicontinuous layer of grain
boundary α which can have a deleterious affect on certain properties, such as tensile
ductility. Thermomechanical processing can be implemented to reduce the tendency
to form the grain boundary α phase.
Mechanical working can cause the grain
boundary α to “relax” to a “broken-up” morphology which makes it less continuous
and less detrimental to final properties [8].
Thermomechanical processing of high strength β alloys is designed to
eliminate these continuous α layers or restrict their negative influence on mechanical
properties. Processing that leads to a bi-modal structure will reduce the influence of
these continuous α layers along β grain boundaries [27].
2.7.3 Bi-Modal (α + β) Processing
When α + β titanium undergoes thermomechanical processing at temperatures
below the β transus and within the α + β region, globularized α grains form from the
α laths. These globules do not have the same orientation relationships within the β
phase as the α laths. During the secondary heat treatment, the existing β will form
30
into α laths during cooling from the dual phase (α + β region). These laths are
commonly known as transformed β [1, 24]. The bi-modal microstructure consists of
equiaxed primary α grains dispersed within a transformed β matrix. The transformed
β matrix is comprised of fine α laths that are separated by β [29].
As seen in the schematic diagram in figure 2.13, homogenization of the
starting lamellar structure occurs in the β phase field. Deformation occurs below the
β phase field in the α + β phase field. Recrystallization occurs within the α + β field,
which produces a mixture of equiaxed α and β grains. This is followed by a final
aging treatment [21]
The cooling rate from step 1 controls the width or thickness of the individual
α lamellae in the β grains and the thickness of the α layer at β grain boundaries. In
step II, the starting lamellar structure is “upset” in the deformation process, and stored
energy (dislocations) is introduced to complete the recrystallization of the binary
phases during step III. The deformation temperature determines texture type, and the
deformation mode determines the texture symmetry [4, 20, 21].
During step III, complete recrystallization occurs as the deformed starting
lamellar structure converts to equiaxed α and β grains. The recrystallized equiaxed
primary α volume fraction and size determine the β grain size. The cooling rate from
the recrystallization temperature determines the width or thickness of the individual α
lamellae and the α colony size of the lamellar structure that formed with cooling
within the equiaxed β grains [4, 21].
After cooling from the recrystallization temperature, the β grains convert back
to a lamellar structure. Compared to fully lamellar structures, these structures have
31
smaller or finer β grain size.
This limits the maximum α colony size and the
maximum length of the α lamellae along with the effective length of the grain
boundary α layer [4, 26].
The aging response of the bi-modal microstructures differs from the fully
lamellar microstructures because of the alloying partitioning effect during the
recrystallization of the bi-modal microstructure [4, 21, 26]. Figure 2.14 shows the bimodal structure at different cooling rates [21].
Figure 2.13 Thermo-mechanical processing for bi-modal microstructures in α + β
titanium [21]
Figure 2.14 Bimodal microstructure of titanium at different cooling rates [21]
32
2.7.3.1 Bi-Modal Microstructure
An important microstructural parameter that affects the mechanical properties
of the bi-modal microstructure is the small β grain size. The small β grain size leads
to a smaller α colony size and thus, shorter slip length. With a decrease in
the α colony size/slip length, there should be an associated improvement in yield
stress, ductility, crack nucleation resistance, and microcrack propagation resistance
[21].
The α colony size is dependent on the cooling rate from the β phase field and
on the β grain size.
For the same cooling rate from the β homogenization
temperature (fully lamellar structure) and recrystallization temperature (bi-modal
structure), a smaller α colony size is seen in the bi-modal microstructure. Due to its
smaller β grain size, the mechanical properties of bi-modal microstructures are not
subject to the negative effect of continuous α layers at the β grain boundaries [21].
Figure 2.15 shows important processing parameters, final microstructural features,
and their influence on mechanical properties for bi-modal microstructures [21].
33
Figure 2.15 Important processing parameters, final microstructural features, and their
influence on mechanical properties for bi-modal microstructures [21]
2.7.3.2 Alloy Partitioning Effect
The aging response of bi-modal microstructures differs from that of the fully
lamellar microstructures due to the alloy partitioning effect in the bi-modal
recystallization treatment. This results in an enrichment of aluminum and oxygen in
the primary α phase, and consequently, the lamellar grains are “softer” than a fully
lamellar structure. The alloying partitioning effect leads to a lower basic strength in
the lamellar grains when compared to the fully lamellar structure. Hence, bi-modal
microstructures have lower creep resistance and lower high cycle fatigue strength at
room temperature in comparison to the fully lamellar structure. The alloy partitioning
effect has a negligible effect on the ductility and fracture toughness [4, 21, 26].
34
2.8 Timetal 550
For purposes of this research, Timetal 550 was used as the designated titanium
alloy. Timetal 550 is a high strength, forgeable α + β alloy; it has superior tensile and
fatigue properties along with good elevated temperature tensile strength and creep
properties up to 400°C [30]. Timetal 550 has an alloy chemistry composition of Ti
4% Al 4% Mo 2% Sn 0.5% Si . Compared to Ti-6Al-4V, the 4% molybdenum serves
as a β stabilizer in place of the vanadium. The molybdenum is heavier than the
vanadium; therefore, diffusional growth in the α lamellae may be sluggish [31].
Timetal 550 is used as a service application for aeroengines and airframe
components in the aerospace industry and high performance engines in the
automotive industry [30].
The chemical compositon and physical properties of
Timetal 550 are outlined in table 2.5 [30].
Table 2.5 Chemical composition and physical properties of Timetal 550 [30]
2.9 Stereology
The central fundamental principle of materials science is that processing
determines microstructure, and microstructure controls and influences the properties
35
and functionality of the materials [32]. Recent advances in developing prediction
models for material properties have promulgated an increased demand for precise
measurements of these features and descriptors. The microstructure is complex and
includes characteristics that can vary significantly and traverse a wide range of scales.
Various standards have been created to characterize these microstructures using
images; but, the actual quantification of these features within α + β titanium alloys is
difficult using conventional technology [29].
Stereology is “the science of the geometrical relationships between a structure
that exists in three dimensions and the images of that structure that are fundamentally
two-dimensional” [33].
The field of stereology describes the geometric
characteristics (grains, voids, etc) of the microstructure’s features in quantitative
terms (amount, numbers, sizes, etc). The theoretical cornerstone of stereology is
rooted in the disciplines of stochastic geometry, integral geometry, global analysis,
and differential geometry [32].
2.10 Serial Sectioning for 3-D Analysis
An immense database of quantified microstructural data would be needed to
design predictive models for α + β titanium alloys. In the current research discipline,
it is not practical or cost effective to invest a large number of man-power hours to
painstakingly examine and extract information from these micrographs.
Some microstructural features, such as volume fraction or area of interface,
can be determined using planar sections.
Particle size distributions and other
parameters can be obtained using “simplifying assumptions” from planar sections.
36
However, there are multiple descriptors, including unit volume, connectivity of
features, size distributions, and spatial distributions that can only be determined using
3-D microstructural images [34].
The 3-D morphology of individual grains, particles, and precipitates
influences the mechanical performance of the material; the connectivity of these
features affects critical aspects of performance, such as toughness and fatigue
resistance. Using 3-D analysis to extrapolate this information and model material
behavior aids in predicting performance. The most practical method for obtaining
this information is through serial sectioning [34].
Serial sectioning is a recognized technique that is used to generate 3-D
microstructural data; multiple science disciplines, including paleontology, biology,
and materials science, use serial sectioning to visualize 3-D object morphologies [35].
Serial sectioning involves carefully removing material layer by layer from a sample.
Each layer is imaged and then the series of images is reconstructed and assembled
using a computer software program [36-38].
Serial sectioning takes a layer of two-dimensional (2-D) images and stacks
them to create the appearance of the microstructure in 3-D. However, the process of
creating these 2-D images is very time-consuming and burdensome due to the large
volume needed to create a 3-D image. In addition, the amount of material that is
sectioned off must be diligently monitored and controlled to reduce variability and
ensure consistency.
Another challenge is encompassing the reconstruction and
assembly of the features lost during the process. Manual chemical etching of the
surfaces is difficult to regulate due to potential variability in enhancing or reducing
37
contrast in the individual sections [35, 36, 39]. Normally, the steps of polishing and
imaging have been done manually or through the use of focused ion beam (FIB),
which can take hours and days to complete.
Computer-based imaging tools provide researchers with a mechanism to
expedite these tasks, which were previously monotonous and laborious. In addition,
these tools afford controls for human bias, assumptions, and subjective judgments
that may influence the results; this provides reproducible data and objective
measurements that are true representations of the microstructure [24, 29, 39]. Figure
2.16 shows cross sections to form a 3-D image [34].
Figure 2.16 Cross sections are used to construct a 3-D shape [34]
Automated serial sectioning provides for high repeatability in the process
steps, including surface preparation.
Automatic mechanical manipulation of the
sample with each step, such as positioning on the microscope stage, improves
38
consistency and reduces variability between images. The use of a motorized digital
microscope lends more rigorous control over field of view, illumination, exposure
time, focus, and contrast level [39].
Searles et al. [24] documented automated stereological procedures for
enhanced speed of dataset acquisition in the quantification of specific microstructural
features in titanium alloys. They used 3-D serial sectioning and automated stereology
procedures for image reconstruction to identify specific minimum and maximum
values in microstructural features.
2.11 Robo-Met.3D
To rectify the time and efficiency constraints and enhance accuracy, the RoboMet.3D was developed for the 3-D generation of microstructures. The Robo-Met.3D
system was custom built at the Air Force Research Laboratory’s Materials and
Manufacturing Directorate with a United States patent application pending. It is a
fully automated robotic serial sectioning device that was originally designed to
quantify the spatial distribution of silicon carbine in aluminum.
Researchers
developed the Robo-Met.3D in response to the difficulty encountered in measuring
spatial distribution using 2-D sections [39, 40]. The Robo-Met.3D is shown in figure
2.17 [39].
This high precision system dramatically reduces the amount of time required
to section and image the sample; this includes specimen preparation, specimen
polishing, digital image capture, and 3-D reconstruction. Custom visualization
software tools are used to capture high-resolution digital images to design and
39
reconstruct accurate 3-D datasets of the sample’s microstructure in near-realtime. The
Robo-Met.3D has high data acquisition rates which provide researchers with a
technique to systematically study microstructural trends and transformation; this
gives researchers the opportunity to examine the effects of heat treatment,
deformation processing and damage evolution [38-40].
Figure 2.17 Robo-Met.3D system with robotic arm, automatic polisher, etching
station, and microscope [39]
The system uses standard polishing techniques to remove between 0.1 and 10
microns of material per section; it can create up to 20 serial sections per hour. Using
a computer program, AxioVision™, settings are inputted and the 6-axis robotic arm
transfers the custom sample to an automatic polisher. Once it has completed the
polishing step, the robotic arm places the sample on the etching platform where the
40
specimen surface is cleaned, etched and dried before being transferred to the optical
microscope. This is a significant improvement from painstakingly polishing and
imaging a sample manually. The accuracy of the section depth can be regulated
through control of polishing time, load, and revolutions per minute [38, 39].
Table 2.6 compares the steps between creating serial sections manually and
automatically using the Robo-Met.3D [39].
Mode of
Operation
Manual
Semiautomated
Automated
a
b
Serial sectioning
process step
Material removal
Polishing by hand
or ‘dimpler’a
Polishing using
automated polisher
Polishing using
automated
polishera
Machining using
micro-millera
Section depth control
Fiducial marks
(micro-indents)b
Fiducial marks or
polishing process
controla,b
Polishing process
controlb
Specimen height
controlb
Specimen surface
preparation
Cleaning, etching and
drying by hand
Cleaning, etching and
drying by hand
Imaging
Manual or motorized
metallograph
Automated cleaning,
etching and drying,
etc.
Automated cleaning,
chip removal
Motorized
metallograph with
autofocus
Dedicated CCD optical
system
Manual metallographa
Rate limiting process
Accuracy-limiting process
Table 2.6 Comparison of steps for creating serial sections manually and with the
Robo-Met.3D [39]
Problem Statement:
Materials property prediction is dependent on one of the fundamental precepts
inherent to materials science: the structure-property relationship. Property prediction
is contingent on the availability of accurate measurements of the structure.
41
Computational material scientists concur that there is a need to integrate experimental
microstructures as starting configurations into various computer models [36]. A 2-D
representation of a microstructure provides a good visual of the material’s
microstructure morphology; however, it lacks spatial and dimensional representation
of the true microstructural geometry [41, 42]. Certain critical aspects and descriptors
of a microstructure, such as precise measurements, parameters, and descriptions of
sizes, shapes, spatial distributions, and interconnectivities, can only be accurately
determined by generating 3-D images [34, 37, 39, 43].
As noted table 2.7, conventional stereological technology involves the
collection of data which is neither precise nor objective. Microstructural features are
complex and arbitrary in their nature. Microstructures are “stochastic”. Each is
unique, and no two microstructures are exactly alike.
They have complex
morphologies, variable locations and orientations, interconnectivity, and nonuniform
spatial distribution.
But yet, microstructural characterization in these standard
stereological tables only provides qualitative information and assumptions that can be
indecisive and vague. These tables fail to demonstrate the interdependent nature of
these microstructural features and their degree of influence on properties. Advanced
metallographic techniques that collect unbiased quantitative information are
straightforward and free of restrictive geometric assumptions [32]. Breakthroughs
and improvements in stereological techniques have provided more advanced
technology for analysis, visualization, and quantification of microstructural
parameters and features.
42
Microstructure governs the mechanical properties in titanium alloys. The
grains and α lath microstructure affect vital aspects of the material’s mechanical
performance, including toughness and fatigue resistance. The ability to examine the
grains and α lath microstructures in a 3-D view is critical to understanding the
behavior of titanium and its alloys [43]. With the availability of the innovative
Robo.Met.3D technology, material scientists now have access to image based
modeling to obtain true representations of the microstructural features.
In addition to 3-D morphology and connectivity of the microstructural
features within a given material, the crystallography of individual grains plays a
critical role in the mechanical response of many materials. Interaction between
nearby grains with different orientations contributes to the mechanical performance of
the material.
Crystallographic orientation must be considered when simulating
mechanical behavior of materials since it can affect elastic and plastic behavior [43].
Table 2.7 Influence of microstructural parameters on mechanical properties of α + β
Ti-alloys and underaged Al-alloys [26]
43
One objective of this research was to examine the results from a 2-D
stereology procedure and compare them to those results obtained from initial serial
sectioning with the focused ion bean (FIB) and Robo-Met.3D. Serial sections and a
3-D reconstruction of titanium using an FIB were created.
A second objective was to develop and document initial procedural steps for
using the Robo-Met.3D with titanium alloys and to create serial sections to observe
the microstructure in a movie.
44
CHAPTER 3
METHOD AND PROCEDURE
3.1 Heat Treatment
The Gleeble 3800® is a fully integrated digital closed loop control thermomechanical simulator created by Dynamic Systems Inc. A Windows-based computer
software program is combined with powerful processors to create controlled physical
stimulation of metallurgical processes. The Gleeble 3800® is a direct resistance
heating system that is capable of high heating rates up to 10,000°C/second. It can
simulate many thermal-mechanical processes and can readily switch between control
variables [44].
Timetal 550 round bar samples were previously heat treated in a Gleeble
3800®. The samples were heat treated above the β transus temperature and air cooled
for a short amount of time and then quenched in ice water [24]. They were provided
in the heat-treated form after the heat treatment schedule found in table 3.1 [31].
45
SAMPLE ID
β
HT
[C]
β Hold Time
[min]
Cooling Rate
[C/s]
Aging
A01
A02
A03
A04
A05
A06
A07
A08
A09
A10
A11
A12
A13
A14
A15
A16
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
2
2
2
2
2
2
2
0.5
0.5
0.5
1
1
1
10
10
10
0.25
0.5
0.75
1
2
3
10
0.25
1
10
0.25
1
10
0.25
1
10
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
Table 3.1 Gleeble ® heat treated A samples [31]
46
Table 3.1 continued
SAMPLE
ID
β HT
[C]
β
Hold
Time
[min]
Cooling
Rate
[C/s]
Sub Trans
HT [C]
Sub Trans
Hold Time
[min]
Cooling
Rate
[C/s]
Aging
B01
B02
B03
B04
B05
B06
B07
B08
B09
B10
B11
B12
B13
B14
B15
B16
B17
B18
B19
B20
B21
B22
B23
B24
B25
B26
B27
B28
B29
B30
B31
B32
B33
B34
B35
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
0.5
0.5
0.5
0.5
0.5
0.5
1
1
1
1
1
1
10
10
0.25
0.25
0.25
0.5
0.5
0.5
0.75
0.75
0.75
1
1
1
2
2
2
3
3
3
10
10
10
0.25
0.25
1
1
10
10
0.25
0.25
1
1
10
10
0.25
0.25
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
925
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
0.25
1
10
0.25
1
10
0.25
1
10
0.25
1
10
0.25
1
10
0.25
1
10
0.25
1
10
0.25
10
0.25
10
0.25
10
0.25
10
0.25
10
0.25
10
0.25
10
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
47
Table 3.1 Continued
SAMPLE
ID
β HT
[C]
β Hold
Time
[min]
Cooling
Rate
[C/s]
Sub Trans
HT [C]
Sub Trans
Hold
Time
[min]
Cooling
Rate
[C/s]
Aging
B36
B37
B38
B39
B40
B41
B42
B43
B44
B45
B46
B47
B48
B49
B50
B51
B52
B53
B54
B55
B56
B57
B58
B59
B60
B61
B62
B63
B64
B65
B66
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
1005
10
10
10
10
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
10
10
0.25
0.25
0.25
1
1
1
10
10
10
0.25
0.25
0.25
1
1
1
10
10
10
0.25
0.25
0.25
1
1
1
10
10
10
925
925
925
925
950
950
950
950
950
950
950
950
950
900
900
900
900
900
900
900
900
900
875
875
875
875
875
875
875
875
875
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
0.25
10
0.25
10
0.25
1
10
0.25
1
10
0.25
1
10
0.25
1
10
0.25
1
10
0.25
1
10
0.25
1
10
0.25
1
10
0.25
1
10
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
500 C, 24 hours
48
3.2 Sample Preparation and Microscopy
The Timetal 550 round bar samples were sliced in two separate locations
within the heat treated region: in the middle of the gage length and then slightly away
from the gage center.
The samples taken from the middle of the gage length were
previously mounted, polished, and imaged [3]. The samples were cut using the EDM
(electric discharge machining) system. The cut pieces were mounted in conductive
bakelite and polished down to 0.05 micron non-crystallizing colloidal silica.
The Timetal 550 samples were imaged using the FEI Sirion scanning electron
microscope (SEM).
The microscope settings for the images were a 15 kV
accelerating beam with a spot size of 4 and a working distance of 5 mm. The images
were taken in back-scattered electron mode (BSE) and were saved as extra high
definition (XHD) tiff images. The tiff images were 3872 x 2904 pixels with a pixel
resolution of 79.56 pixels/micron. Four to eight images were randomly taken on each
sample. The magnification ranged from 500x to 8000x depending on the size of the
microstructure. A representation of the XHD tiff image taken with the Sirion SEM
can be observed in figure 3.1 A.
3.3 Stereology Set up
The Timetal 550 SEM and optical images were saved on a Mac G5 computer
and external hard drive due to the size of each individual image as well as the volume
of images taken. The automated stereology procedures were created to help minimize
man hours of work necessary to measure and characterize the titanium microstructure
[45]. The automated procedure was created using Adobe Photoshop CS™ and Fovea
49
Pro™ by setting up actions for each stereological measurement. A batch process was
set up to run each image and save the data on the Mac G5 desktop automatically.
3.4 Characterization
3.4.1 Thresholding α Laths
The grayscale Sirion SEM images were thresholded to black and white images
before any quantification of the microstructure occurred. Thresholding of the images
was completed in Adobe Photoshop CS ™ and Fovea Pro ™ by changing the levels
of gray and maximizing low contrast. This was done by setting bright and dark limits
using the histogram and changing the output levels within the range of 0 to 255, zero
being black. The α laths were thresholded to black while the β ribs were thresholded
to white. The output levels were chosen for each individual image to ensure the most
accurate results would be obtained during the characterization of the images.
During the thresholding action, the secondary α was removed so the volume
fraction and lath size of primary α could be determined. Removal of the secondary α
was completed by a series of steps involving Gaussian blur, Classic Morphology and
Euclidean Distance Mapping (EDM) Based Morphology in Fovea Pro ™.
The
Gaussian blur feature was used on the images to reduce detail levels to help bring out
the dark colored laths. The Classic Morphology feature was used to clean up small
pixel-sized areas in the image. The features of a certain pixel size, between 500-1000
pixels, were then rejected to eliminate the secondary α laths.
50
A
B
Figure 3.1 Timetal 550 B01 Sirion SEM image (A) and thresholded (B)
51
The primary α laths were then dilated back to their original size using the
EDM Based Morphology to clean up the image. The initial and final images of the
thresholding action can be observed in figure 3.1.
3.4.2 Volume Fraction α and Lath Thickness
The thresholded Timetal 550 Sirion images were used to determine the
volume fraction of α. To determine the volume fraction, an automated action was set
up with Fovea Pro™ and Adobe Photoshop™. Global Stereological Data in Fovea
Pro ™ determined the area fraction of the thresholded black lath region.
The original Sirion SEM images were saved without micron markers to allow
for more area for characterization, so the images needed to be calibrated before the α
lath thickness could be calculated. The Measure Intercepts feature in Fovea Pro ™
was used to calculate the thickness. The action overlays a grid of lines beginning at
an angle of 5o and when the line crosses over a thresholded lath region, it remains.
Any lines that remained in the white β region were omitted. All of the remaining
lines were measured and an average was calculated. This process was completed
every 5o until it reached a full 180o. The mean inverse intercept was calculated and
inserted into the following equation to determine lath size.
Lath size = ___________1_____________
1.5* mean inverse intercept
52
As noted above, the value is derived from the concept that the thickness of a set of
infinite plates can be estimated using line segments formed by the intersection with a
series of random lines [29].
3.5 Serial Sectioning for 3D Microstructures
The Robo-Met.3D is a new fully automated serial sectioning that has never
been used on titanium samples.
Therefore, more time was allotted to sample
preparation and identification of the most favorable process to complete the serial
sectioning. The samples were prepared for this system using a core drill on the EDM.
The sample pieces were approximately 2-3 millimeters in diameter and approximately
6 millimeters in height. The mounts were between 12-13 millimeters in diameter and
20 millimeters in height.
Sample specimens were placed in three different mountings to determine
which would produce the best optical results. The samples were mounted in 3 ways:
epoxy with the specimen extending out through the epoxy (figure 3.2 A), a titanium
base where the sample was spot welded to the base (figure 3.2 B), or a titanium base
with a core drilled center where the sample was crystal bonded into the drilled hole
(figure 3.2 C).
53
A
B
C
Figure 3.2 Schematic drawing of the 3 types of mountings used for the Robo-Met.3D
system. (A): Epoxy stub (B): Titanium stub with spot welded sample (C): Titanium
stub with embedded sample
Due to early software problems with the Robo-Met.3D system, many of the
initial procedural steps were completed using Robo-Met.3D manually. To determine
what would produce optimal data from the Robo-Met.3D, different runs were created
using the AxioVision™ software. The polishing time and speed and etching and
cleaning time were changed with each run. To determine the optimal polishing time,
the samples were marked with a fiducial mark using a micro hardness tester where the
angle of the indent was 136o. Knowing the angle, the depth of the fiducial mark was
determined. After each run, the fiducial mark was imaged optically and the change in
depth was calculated.
The initial full run was completed on the Robo-Met.3D using a Ti-6Al-4V
sample with a bi-modal microstructure. The sample was mounted into epoxy. The
polishing speed used was 50 RPM for 4 minutes. The specimen was etched with a
Kroll’s solution comprising of 1 ml of HF, 1 ml of HNO3, and 100 ml of H2O. The
etching time was set to 9 seconds. The optical images that were taken at 0.25 micron
slices using the system were then cropped and aligned using Adobe Photoshop™ to
54
make each image line up with one another. The initial image size was 272 μm x 203
μm (2584 pixels x 1936 pixels). A serial section image before and after the α globs
were colored can be found in figure 3.3.
The globular α was then traced on 68 μm x 50 μm (1/4 of the initial image) of
each of the 70 images and then 205 μm x 160 μm (1/2 of the initial image), 135 μm x
102 μm (3/4 of the initial image), and 272 μm x 203 μm (100% of the initial image)
were traced for every 10th image (image #1, 10, 20, etc.). The volume fraction
globular α results were observed for each image. These volume fraction results were
then put into a graph to observe the differences in volume fraction between each
image.
3.6 FIB
The Timetal 550 sample selected for serial sectioning in the FIB had high area
per volume of prior β grain size and approximately 50% colony and 50%
basketweave microstructure. The sample was polished down to 50 microns using
0.05 non-colloidal silica on a Chemomet pad. While mounted to an aluminum stub,
the sample was tilted to a 52o angle in NOVA with a working distance of 5mm. An
area of 86 microns thick and 70 microns wide was chosen for the serial sectioning.
The top of the selected area was coated with platinum to protect the surface during
the milling process. The serial sectioning of the section was set up to remove 400 nm
per slice.
55
The 30 kV ion beam cut through the sample at 9000 Pico amps. A 2-D
sectioned image can be observed below in figure 3.4. A collection of the serial
sections can be found in figure 3.5. The collection of serial sectioned images was
used to create the 3-D reconstruction.
The images acquired from the serial sectioning were aligned using Adobe
Photoshop CS ™ and then 9 α laths were traced and colored to ensure a good
representative 3-D reconstruction of the microstructure. The images with the colored
α laths where then put into IMOD [46], which is a program designed for image
processing and modeling for 3-D reconstructions of serial sections.
56
A
B
Figure 3.3 Robo-Met.3D serial section image #70 before (A) and after (B) α globs
were colored
57
In IMOD, individual laths on each image were considered contours. Each of
these contours were meshed together and colored to give a 3-D reconstruction that
can be rotated on an axis.
The two different 3-D reconstructions that were created can be observed in
figures 3.6 and 3.8.
The first reconstruction shows a 3-D representation of the
basketweave microstructure and the interaction between each lath. The second 3-D
reconstruction was created to observe the possibility of sympathetic nucleation within
the grain. The 2-D images associated with the sympathetically nucleated laths can be
observed in figure 3.7. These α lath thickness and spacing between these α laths on
the 3-D reconstruction was measured in Adobe Photoshop CS™.
Figure 3.4 Ti-6Al-4V image taken with the NOVA FIB
58
59
Figure 3.5 Serial Sections of Ti-6Al-4V layers created with the NOVA FIB
A
B
Figure 3.6 3-D reconstruction of Ti-6Al-4V α laths from serial sections taken with
the NOVA FIB shown at different angles (A) and (B)
60
A
B
C
Figure 3.7 Serial sectioning images from the FIB of Timetal 550 showing the
appearance of α laths in the center of the grain
61
A
B
Figure 3.8 3-D reconstruction of Ti-6Al-4V α laths from serial sections taken with
the NOVA FIB (A) and (B)
62
CHAPTER 4
RESULTS AND CONCLUSIONS
4.1 Stereology Results
Analysis of the data obtained from the heat treated Timetal 550 showed that a
uniform microstructure was not visible throughout the gage length of the material.
Figure 4.1 shows images of the B08 sample taken at different locations along the
gage of the specimen.
This can be observed in table 4.1, which compares the
resultant differences from the two locations along the gage. In table 4.1, the A
column displays the results from the sample obtained from the center of the gage,
while the B column summarizes the results from the sample obtained away from the
gage center. On the latter sample (B), the average volume fraction of α laths appears
to be higher. This is a result of slower cooling on the material farther away from the
gage center. Also, there is secondary α in sample image B. If this procedure were to
be replicated, the findings may not be reproducible or consistent with these, and thus,
the final results will be different.
63
The variation in microstructure along the gage length of a sample heat treated
in the Gleeble® could potentially create problems when the samples undergo
mechanical testing. The variation could provide results that would not necessarily be
a clear and accurate representation of the relationship between the mechanical
properties and microstructure itself.
64
A
B
Figure 4.1 B08 Images taken at different locations along the gage of a Timetal 550
specimen. A) Center of gage. B) Away from center of gage
65
A
Sample
Average
Alpha
area
Fraction
A01
A02
A03
A04
A05
A06
A07
A08
A09
A10
A11
A12
A13
A14
A15
69.618
67.831
73.041
70.762
N/A
75.169
74.082
75.580
76.390
75.827
77.350
74.070
74.956
69.564
72.883
A16
71.104
B
STDEV
Average
Lath Size
(microns)
STDEV
1.969
1.317
4.746
3.202
N/A
3.746
2.578
2.217
4.671
2.747
3.407
1.998
3.345
4.835
3.359
1.310
1.176
1.266
1.167
N/A
1.191
1.192
1.824
1.614
1.287
1.988
1.735
1.092
1.207
1.053
0.169
0.081
0.118
0.095
N/A
0.071
0.129
0.190
0.255
0.185
0.251
0.501
0.154
0.181
0.080
3.651
0.987
0.114
Sample
Average
Alpha
Area
Fraction
A01
A02
A03
A04
A05
A06
A07
A08
A09
A10
A11
A12
A13
A14
A15
81.990
83.814
78.061
78.716
84.033
85.874
84.215
82.003
79.113
82.956
85.454
84.084
83.992
83.068
79.890
A16
83.977
STDEV
Average
Lath Size
(microns)
STDEV
2.497
1.491
2.089
0.858
2.295
1.266
2.494
1.134
3.069
2.616
2.565
2.529
2.241
2.183
2.671
1.731
1.074
1.596
7.138
2.228
2.256
2.017
2.892
0.819
1.999
3.106
2.324
1.677
2.906
1.048
0.594
0.148
0.543
0.286
0.388
0.113
0.767
0.346
0.088
1.999
0.391
0.265
0.114
0.763
0.475
2.418
1.024
0.200
Table 4.1 α lath data obtained from the Gleeble 3800 ® heat treated samples. Column
A data was taken from the center of the gage and column B data was obtained from
samples taken away from the center of the gage
66
Table 4.1 Continued
A
Sample
Average
Alpha
Area
Fraction
B01
B02
B03
B04
B05
B06
B07
B08
B09
B10
B11
B12
B13
B14
B15
B16
B17
B18
B19
B20
B21
B22
B23
B24
B25
B26
B27
B28
B29
B30
B31
B32
B33
B
Sample
Average
Alpha
Area
Fraction
0.279
0.203
0.098
0.751
0.194
0.047
0.436
0.147
0.075
0.267
0.143
0.230
0.306
0.357
0.163
0.246
0.174
0.270
0.357
0.318
0.102
0.374
0.123
0.185
0.149
0.338
N/A
0.204
0.142
0.111
0.088
0.360
B01
B02
B03
B04
B05
B06
B07
B08
B09
B10
B11
B12
B13
B14
B15
B16
B17
B18
B19
B20
B21
B22
B23
B24
B25
B26
B27
B28
B29
B30
B31
B32
0.062
B33
STDEV
Average
Lath Size
(microns)
STDEV
75.849
73.351
75.662
76.606
73.084
75.081
73.672
75.343
77.645
76.069
76.392
77.356
80.188
76.739
78.409
77.211
77.461
80.374
78.317
78.003
80.332
77.548
77.739
82.161
37.637
84.547
N/A
83.758
73.040
76.992
72.158
72.463
2.246
2.438
3.954
4.444
4.281
1.631
1.943
1.820
0.588
1.757
2.223
3.120
1.675
1.517
4.116
4.895
1.786
2.347
2.105
1.118
1.487
2.749
4.824
0.809
5.830
0.781
N/A
0.787
2.734
0.541
3.676
2.286
7.717
1.490
1.167
3.396
1.379
1.235
6.341
1.868
1.345
1.632
1.566
1.602
4.135
6.940
1.368
5.269
3.140
2.254
5.363
5.299
1.871
5.925
1.281
5.088
3.545
7.361
N/A
6.669
1.162
6.875
1.048
2.686
76.254
1.380
1.396
67
STDEV
Average
Lath Size
(microns)
STDEV
80.190
83.266
84.911
74.284
81.602
81.650
80.142
76.287
82.184
81.978
76.566
79.492
78.618
76.631
85.528
78.001
81.978
85.269
77.154
83.768
86.683
85.122
86.908
77.735
31.231
81.273
83.804
80.148
83.116
79.148
80.122
80.524
2.170
2.250
2.481
2.301
1.171
5.512
1.096
1.104
3.594
1.729
3.322
2.762
3.502
2.025
3.856
1.265
2.524
2.175
1.087
1.630
2.204
1.315
2.430
1.284
21.922
0.823
1.945
1.755
2.175
0.551
1.910
2.140
6.865
2.622
0.671
1.284
1.420
2.185
8.627
6.412
1.404
1.314
0.913
1.252
3.379
6.780
0.654
4.432
2.281
1.642
6.912
1.656
1.011
1.217
0.570
6.817
2.219
6.641
0.615
1.954
0.622
7.067
0.754
1.040
0.326
0.569
0.518
0.279
0.218
1.001
0.257
0.127
1.866
0.387
0.227
0.180
1.897
1.537
0.084
1.693
0.575
0.604
0.251
0.960
0.121
0.239
0.097
0.328
2.027
0.228
0.108
0.471
0.153
0.267
2.248
0.194
79.108
2.833
0.754
0.108
Table 4.1 Continued
A
Sample
Average
Alpha
Area
Fraction
B34
B35
B36
B37
B38
B39
B40
B41
B42
B43
B44
B45
B46
B47
B48
B49
B50
B51
B52
B53
B54
B55
B56
B57
B58
B59
B60
B61
B62
B63
B64
B65
B66
B
Sample
Average
Alpha
Area
Fraction
0.304
0.159
0.189
0.122
0.156
0.315
0.253
0.016
0.086
0.100
0.121
0.069
0.017
0.180
0.102
0.354
0.232
0.504
1.179
0.924
0.322
1.297
N/A
0.243
0.388
1.191
0.337
0.348
0.192
0.212
0.326
0.067
B34
B35
B36
B37
B38
B39
B40
B41
B42
B43
B44
B45
B46
B47
B48
B49
B50
B51
B52
B53
B54
B55
B56
B57
B58
B59
B60
B61
B62
B63
B64
B65
0.156
B66
STDEV
Average
Lath Size
(microns)
STDEV
77.345
78.104
77.260
77.365
78.793
79.737
76.242
72.671
76.233
77.161
76.837
82.223
74.811
79.320
83.556
72.539
74.886
72.363
78.881
80.236
56.244
77.755
81.351
78.297
80.558
76.829
74.722
73.942
75.187
73.974
76.888
73.009
1.459
7.357
1.535
2.965
0.889
2.814
3.094
0.720
2.291
0.962
2.582
3.132
1.429
1.095
1.629
1.680
2.377
3.823
0.589
2.195
2.042
1.499
N/A
3.154
1.593
0.596
3.850
3.242
2.355
2.637
2.556
0.331
4.450
1.194
6.710
1.285
1.850
2.299
1.667
1.222
1.212
1.805
1.415
0.495
1.555
1.636
0.589
9.530
5.394
3.784
4.360
4.395
3.736
3.650
1.988
1.532
4.914
3.516
2.935
1.830
1.917
3.258
2.013
1.671
69.029
3.759
3.272
68
STDEV
Average
Lath Size
(microns)
STDEV
79.857
83.066
77.509
78.779
81.529
80.853
83.268
85.344
87.687
79.927
82.099
87.623
80.997
78.142
84.615
82.217
76.320
78.385
80.275
71.385
50.660
80.820
82.440
76.517
79.327
79.430
69.229
79.572
75.521
77.821
80.544
78.618
3.375
2.209
2.464
3.013
2.110
2.891
1.335
2.859
1.996
1.397
3.653
4.171
3.003
3.772
5.186
1.502
2.940
2.317
1.003
2.134
2.763
1.039
1.681
2.289
1.474
3.461
3.443
2.774
1.889
1.061
1.178
1.759
3.164
0.467
5.942
1.106
1.848
1.825
1.617
1.845
0.426
2.350
1.232
0.678
1.684
1.358
0.556
8.066
5.384
5.899
6.777
5.912
3.878
6.870
1.052
1.394
6.721
5.385
4.582
5.525
3.992
3.161
4.020
3.786
1.394
0.346
0.523
0.113
0.661
0.228
0.195
1.085
0.057
1.201
0.590
0.629
0.403
0.171
0.437
0.478
1.004
0.337
0.233
0.319
0.833
0.427
0.218
0.767
0.464
0.325
0.373
0.466
0.217
0.149
0.072
0.212
72.203
3.878
3.147
0.377
4.2 Robo-Met.3D Results
Since titanium had not been previously used with the Robo-Met.3D system, a
majority of the initial work was focused on developing procedures for creating good
optical serial sections. Different aspects of the system were tested. The different
mountings, speed of the polishing step on the Allied Multiprep system, type of
polishing paper, and the cleaning and etching times were varied and evaluated to
identify the most advantageous procedure.
The use of diamond lapping film to polish samples with the Robo-Met.3D
system was considered.
However, titanium does not polish well with diamond
lapping film since the sample scratches easily with this type of paper. A Chemomet
pad with 0.05 non-colloidal silica was used as a substitute for the diamond lapping
film.
Time intervals were varied and adjusted with the sample mounted in epoxy to
establish how much material was being removed respectively in relation to time
lapsed during the polishing step. The speed of the Allied Multiprep was determined
to be optimal between 20 and 100 RPM depending on sample size. Graphical data
showing the amount of material removed versus time can be observed in figures 4.2
and 4.3 for 20 RPM and 50 RPM.
These results are only provided for those
specimens where the sample was extending out through the mounting material. Due
to system problems with the Robo-Met.3D system, this data has not yet been
collected for the larger samples.
69
20 RPM
3
Amount removed (microns)
2.5
2
1.5
1
0.5
0
150
200
250
300
350
400
Time
Figure 4.2 Amount of material removed versus Time at 20 RPM for the Multiprep on
the Robo-Met.3D system
50 RPM
3.5
Amount removed (microns)
3
2.5
2
1.5
1
0.5
150
200
250
300
350
400
Time (sec)
Figure 4.3 Amount of material removed versus Time at 50 RPM for the Multiprep on
the Robo-Met.3D system
70
The smaller samples had less area to be polished, so theoretically it would
have been more time efficient to use these samples. However, several problems were
encountered when using these particular samples. As discussed in chapter 3, each of
the different titanium mountings were polished and then imaged. When the smaller
samples were secured with epoxy or spot welded to the base of the stub, there was
protruding sample material that got caught and subsequently ripped the polishing
paper. However, in the titanium stub with the core drilled hole, the surface of the
sample was level with the surface of the mount. Even though the sample was larger,
it was easier to polish since the sample was embedded within the mount, and the
entire surface was planar.
In addition, the smaller samples were only a few millimeters in length so they
tended to curve along the edges. This negatively affected the quality of the optical
images, especially at higher magnifications. These samples were not planar, so half
of the images were in focus while the remaining images were “blurred.” In figure 3.3
A, blurring of the image is visible in the upper corners. The polishing time of the
larger samples took four times longer to grind away the same thickness of material
compared to the smaller samples; however, the larger samples had better quality
images.
There were a few obstacles that needed to be overcome during the initial runs
on the Robo-Met.3D. As can be seen in figure 3.3 A, along with the blurring due to a
nonplanar sample, the top right corner of the image was burned during the etching
process. This was most likely caused by a constant flow of etchant being introduced
71
into the etching basin. To fix the burning of the sample, the flow process was turned
off during etching.
Another problem occurred during the cleaning step. The cleaning step of the
Robo-Met.3D process had been inconsistent as shown in figure 4.4 A, where the
image appears to have a film covering the surface. To rectify this problem, a second
cleaning station was been introduced into the system to allow for multiple cleaning
steps.
The Robo-Met.3D serial sectioning procedure was used on a Ti-6Al-4V
specimen with a bimodal microstructure.
A total of 70 images were taken
collectively at approximately 0.25 microns per layer. After the globular α were traced
on 68 x 50 μm of the image on all 70 images, and every 10th image for 135 x 102 μm,
205 x 160 μm and 272 x 203 μm images, the results were charted and tabulated to
show the average volume fraction of globular α. The graph showing the results of
volume fraction α vs. image # can be observed in figure 4.5.
Image Size
(microns)
Average Volume
Fraction Alpha (%)
Standard
Deviation
68 x 50
135 x 102
205 x 160
272 x 203
54.1649
64.6044
65.4362
68.2277
6.3345
6.8552
6.6215
4.4642
Table 4.2 Average volume fraction of globular α
72
The data in table 4.2 (above) shows that the average volume fraction of
globular α significantly increases from the 68 μm x 50 μm image to the 272 μm x 203
μm image. There is also a dramatic decrease in volume fraction α between images 40
and 50 as can be seen in figure 4.5. This variability and inconsistency in the results
show the variation that can occur with 2-D image stereology. The random selection
of images produces fluctuating variations that can affect the volume fraction
calculation. The results also show that this applies to the size of the image taken.
The volume fraction increases as the sample gets larger, and the standard deviation
goes down.
When using standard stereology procedures, this can “beg” many
questions. How many images and what size of area is necessary to obtain a good
representation of the microstructure? Since mechanical properties are directly related
to microstructure, questions such as these reinforce the need to incorporate 3-D
microstructure reconstructions into materials science.
73
A
B
Figure 4.4 Robo-Met.3D images A) Ti-6Al-4V image number 40 B) Ti-6Al-4V
image number 50
74
75
35
40
45
50
55
60
65
70
75
80
0
10
20
30
40
50
Ti-6Al-4V Sample
60
70
272x203
205x160
135x102
68x50
Figure 4.5 Ti-6Al-4V chart showing the variation in area fraction of alpha in each serial section Robo-Met.3D image
Area Fraction
4.3 FIB Results
A movie was created from the NOVA FIB serial sectioning, and 3-D
reconstruction of the microstructure was done, as described in chapter 3. When
examining these serial section movies, nucleation of the α laths is noted at the prior β
grain boundary as well as elsewhere within the grain. This initial 3-D reconstruction
of the Timetal 550 alloy shows some colonies, which initially formed at the grain
boundaries, growing into one another as they extend into the grain. The sequential
steps of nucleation from grain boundary can be observed in the 2-D serial section
movie.
The differences between the 2-D images and the 3-D reconstruction can be
observed in the images found in chapter 3.
With 2-D images, only planar
measurements and observations are available at the external surface. Using planar
measurements from a 2-D structure, connectivity, size distribution, and spatial
dimensions can be determined for a 3-D image, such as the change in lath size and
shape. These features are critical in determining mechanical properties; lath size
affects tensile strength, ductility, and fatigue crack initiation resistance.
At one point during the serial sectioning, three laths form in the center of the
grain in a parallel alignment as noted in figure 3.7 of chapter 3. While nucleation
preferentially occurs at the grain boundary due to the free energy, it appears these
laths nucleated elsewhere. The opacity was reduced to 10% in figure 4.6 to show the
tracing of the laths in Adobe Photoshop CS™. These laths are not in direct contact
with another lath, which would have been the result of interface nucleation.
76
While it would not be definitively known unless TEM work was completed on
the sample, this might be a result of sympathetic nucleation whereby the laths form at
an interphase boundary within the grain. Since these laths form and extend in the
same direction, there is a possibility of sympathetic nucleation.
The average
thickness and the average spacing of α laths in a 3-D image were measured in Adobe
Photoshop CS™ and the results are found in figure 4.7 and tables 4.3 and 4.4. The
similarities in lath sizes would suggest that the α laths were nucleated at identical
temperatures during cooling. As noted by Aaronson et al [47], it appears that the
system is “extending significant ‘sympathy’ toward the nucleation process”.
Furthermore, these authors noted that the formation of laths in the same direction
during sympathetic nucleation could lead to a favorable strain reduction within the
matrix.
One of the important microstructural features in β-processed α+β Ti alloys is
the allotriomorphic grain boundary α that can decorate the prior β grain boundaries.
Such grain boundary α is thought to not only play a significant role in the evolution of
microstructure, but also can significantly impact mechanical properties such as tensile
strength and fracture toughness. With regard to the evolution of microstructure, one
can observe from two-dimensional micrographs in microstructural evolution studies
that the grain boundary α often forms prior to any intragranular α laths - either colony
or basketweave. Additionally, the presence and thickness of grain boundary α can
often be correlated with whether a microstructure is predominately colony (thick
grain boundary α) or basketweave (thin to no resolvable grain boundary α) [31].
Thus, theories have been developed relating allotriomorphic grain boundary α and
77
side-plate formation, including applying the Mullens-Sirkirka instability. The
nucleation of such grain boundary α is often thought to occur at either grain boundary
triple points or corners. Within the FIB dataset (a two dimensional micrograph is
shown in fig. 4.8a), there exists a grain boundary that was subsequently reconstructed
in three dimensions. As can be seen in fig. 4.8b, the prior β grain boundary is covered
with what appears to be five discrete grain boundary α allotriomorphs. In addition,
the grain boundary triple points are clearly visualized. Interestingly, if one assumes
the center of the features to be the nucleation site, followed by a combination of
diffusion controlled in-plane growth (e.g., along the grain boundary) and out of plane
thickening, one observes that there are nucleation sites that occur within the grain
boundary between two neighboring grains, indicating that nucleation events are not
strictly limited to triple "points" (actually 1D lines) and quad junctions (0D). Future
three-dimensional orientation microscopy work will be required to determine whether
there are crystallographic differences between the allotriomorphic plates, and TEM
work will be required to determine the nature of the boundaries between the
allotriomorphic. As can be seen in fig. 4.8c, some of the grain boundaries that appear
tortuous in two-dimensions exhibit ridges in three dimensions. This particular ridged
region corresponds to the grain boundary located in the upper right portion of fig.
4.8(a).
78
Figure 4.6
nucleation
FIB serial section of Timetal 550 showing possible sympathetic
79
1 2 3
4 5 6
Figure 4.7 3-D α laths of Timetal 550 created in IMOD
SPACE BETWEEN LATHS IN MICRONS
Average
STDEV
Between
α lath 12
Between
α lath 23
Between
α lath 45
Between
α lath 56
0.876
0.030
0.832
0.045
0.697
0.042
0.796
0.123
Table 4.3 Space between the α laths from figure 6.7
α LATH THICKNESS
Average
STDEV
α Lath
1
0.699
0.037
α Lath
2
0.909
0.059
α Lath
3
0.839
0.020
Table 4.4 α lath thickness from figure 6.7
80
α Lath
4
0.854
0.025
α Lath
5
0.995
0.060
α Lath
6
0.926
0.127
(a)
(b)
(c)
Figure 4.8 Grain boundary α allotriomorphs in 2-D (a) and 3-D (b,c)
81
CHAPTER 5
SUMMARY AND FUTURE WORK
5.1 Summary
Initially, several months were spent focused on resolving problems with the
functioning of the Robo.Met.3D. The software was not communicating properly with
the robot itself, which hindered progression of the research undertaken.
Discrepencies with the stereological results from Ti-6Al-4V were found with
the data obtained from the Robo-Met.3D. There were significant differences in the
average volume fraction of equiaxed α due to the variability of the results as shown in
figure 4.5.
Furthermore, discrepancies in the Timetal 550 images obtained from
different heat treated areas could raise problems for future research. Due to the
inconsistency of the collected data, similar results may not be reproducible with a
replicated procedure.
82
Serial sectioning movies were created with the Robo-Met.3D system and the
FIB. Three-dimensional reconstructions of α laths were created using the FIB serial
sections and the IMOD computer program. Three α laths were noted in the center of
the grain. They were aligned in a parallel orientation and did not have a clear
identifiable origin on the grain boundary. When examining these microstructures, it
appeared that they may have been the result of sympathetic nucleation.
5.2 Future Work
In 2003, Spowart published current and projected capabilities for the RoboMet.3D as outlined in table 5.1 [38].
At that time, Spowart had predicted that the
Robo-Met.3D would be used for titanium alloy material systems. As noted in this
research, the use of Robo.Met.3D for microstructural analysis of titanium is still in
the infantile stages. Specifically, as a result of these findings, future investigation
should include identifying a new procedure to mount and polish the sample to prevent
sample curvature due to the polishing step.
The future of materials science includes creating many more serial sections
using the Robo-Met.3D; therefore, new, faster, and more efficient procedures will
need to be developed for coloring in the desired microstructural features in Adobe
Photoshop CS™. At present, this step is the most time consuming whereby it could
potentially requires days to color in the desired features.
As the Robo-Met.3D is improved, new projected capabilities can be identified
and incorporated into the robot’s design process. For example, Spowart [39] suggests
that a magnetic probe could be scanned over the specimen while the optical images
83
are being collected to generate a “corresponding map of magnetic domains” that
could be constructed into a 3-D magnetic representation.
Furthermore, research on 3-D microstructures involving secondary α that
forms within the grains should also be considered. This may be difficult due to the
small size of the secondary α, however, it is important to examine these features and
to describe the effects they have on the mechanical properties of the specific sample
material.
Table 5.1 Current and projected capabilities of Robo-Met.3D [38]
84
Examination and analysis of the 3-D morphology of a finished titanium
surface provides critical information regarding microstructural properties, material
design, and end use application.
Three-dimensional spatial and crystallographic
information obtained from image-based modeling can be used to determine critical
microstructural features where failure or fracture is likely to occur within the given
material. The use of this information can be used to tailor the microstructure to meet
material property requirements for performance in commercial, military, aerospace,
and medical applications [43].
85
REFERENCES
1. Joshi, V. Titanium Alloys: An Atlas of Structures and Fracture Features.
2006. Boca Raton, Fla.: CRC Press. Taylor and Francis Group.
2. Rosenberg, H. Titanium Production and Refining. In K.H. Jürgen Buschow,
R. Cahn, M. Flemings, and B. Ilschner (Editors). Encyclopedia of Materials:
Science and Technology. 2001. New York: Elsevier.
3. Schweitzer, P. Fundamentals of Metallic Corrosion: Atmospheric and Media
Corrosion Metals. 2006. Boca Raton, Fla.: CRC Press. Taylor and Francis
Group.
.
4. Lutjering, G. and Williams, J. Titanium. 2003. New York: Springer-Verlag.
5. Donachie, M. (Ed.). Titanium: A Technical Guide (2nd Ed.). 1988. Metals
Park, Ohio: ASM.
6. Caron, R. and Staley, J. Effects of Composition, Processing, and Structure on
Properties of Nonferrous Alloys. In ASM Handbook: Volume 20 Materials
Selection and Design. 1997. Electronic File: ASM International.
7. Froes, F. H. Titanium Alloys: Properties and Appplications. In K.H. Jürgen
Buschow, R. Cahn, M. Flemings, and B. Ilschner (Editors). Encyclopedia of
Materials: Science and Technology. 2001. New York: Elsevier.
8. Froes, F.H. Titanium Alloys: Thermal Treatment and Thermomechanical
Processing. In K.H. Jürgen Buschow, R. Cahn, M. Flemings, and B. Ilschner
(Editors). Encyclopedia of Materials: Science and Technology. 2001. New
York: Elsevier.
9. Koch, G. SCC of Titanium Alloys. In ASM Handbook: Volume 19 Fatigue
and Fracture. 1996. Electronic File: ASM International.
86
10. Freese, H.L., Volas, M.G., Wood, J.R., and Textor, M. Titanium and its
Alloys in Biomedical Engineering. In K.H. Jürgen Buschow, R. Cahn, M.
Flemings, and B. Ilschner (Eds). Encyclopedia of Materials: Science and
Technology. 2001. New York: Elsevier.
11. McCann, M. and Fanning, J. Designing with Titanium Alloys. In Totten, G.,
Xie, L. and Funatani, K. (Eds.). in Handbook of Mechanical Alloy Design (p.
539-582). 2004. New York: Marcel Dekker, Inc.
12. Froes, F.H. Titanium Alloying. In K.H. Jürgen Buschow, R. Cahn, M.
Flemings, and B. Ilschner (Editors). Encyclopedia of Materials: Science and
Technology. 2001. New York: Elsevier.
13. Boyer, R. (Ed.). Introduction and Overview of Titanium and Titanium Alloys:
Alloy Systems. In Metals Handbook Desk Edition. 2002. Electronic File:
ASM International.
14. Ivasishin, O.M. and Markovsky, P.E. Enhancing the Mechanical Properties of
Titanium Alloys with Rapid Heat Treatment, 2006. JOM. 48: p. 48-52.
15. Rath, B.B. Kinetics of Nucleation and Growth Process. Materials Science and
Engineering B, 1995. B32: p. 101-106.
16. Martin, J. W. Materials for Engineering (3rd Ed.). 2006. Cambridge,
England: Woodhead
17. Kar, S. “Modeling of Mechnical Properties in Alpha/Beta Titanium Alloys.”
Dissertation, The Ohio State University, 2004.
18. Antolovich, S. Alloy Design for Fatigue and Fracture. In ASM Handbook:
Volume 19 Fatigue and Fracture. Electronic File: ASM International.
19. Katarov, I., Malinov, S., and Sha, W. Finite Element Modeling of the
Morphology of β to α Phase Transformation in Ti-6AI-4V Alloy.
Metallurgical and Materials Transactions A, April 2002. 33A: p. 1027-1040.
20. Sauer, C. and Lütjering, G. Thermo-mechanical Processing of High
Strength Β-titanium Alloys and Effects on Microstructure and Properties.
Journal of Materials Processing Technology, 2001. 117: p. 311-317.
21. Lütjering, G. Influence of Processing on Microstructure and Mechanical
Properties of (α + β) Titanium Alloys. Materials Science and Engineering A,
1998. A243: p. 32-45.
87
22. Menon, E. and Aaronson, H. I. Morphology, Crystallography and Kinetics of
Sympathetic Nucleation. Acta Metallurgica, 1987. 35: p. 549-563.
23. Doherty, R.D., Hughes, D.A., Humphreys, F.J., Jonas, J.J, Jensen,
D.J., Kassner, M.E., et al. Current Issues in Recrystallization: A Review.
Materials Science and Engineering A, 1997. A238: p. 219-274.
24. Searles, T., Tiley, J., Tanner, A., Rollins, B., Lee, E., Kar, S. et al. Rapid
Characterization of Titanium Microstructural Features for Specific Modelling
of Mechanical Properites. Measurement Science and Technology, 2005. 16:
p. 60-69.
25. Semiatin, S.L., Knisley, S.L., Fagin, P.N., Zhang, F. and Barker, D.R.
Microstructure Evolution During Alpha-Beta Heat Treatment of Ti-6AI-4V.
Metallurgical and Materials Transactions A., 2003. 34A: p. 2377-2386.
26. Lütjering, G. Property Optimization Through Microstructural Control in
Titanium and Aluminum Alloys. Materials Science and Engineering A, 1999.
A263: p. 117-126.
27. Sauer, C., and Lütjering, G. Influence of α Layers at β Grain Boundaries on
Mechanical Properties of Ti-alloys. Materials Science and Engineering A,
2001. A319-321: p. 393-397.
28. Chrapinski, J. and Szkliniar, W. Quantitative Metallography of Two-Phase
Titanium Alloys. Materials Characterization, 2001. 46: p. 149-154.
29. Tiley, J., Searles, T., Lee, E., Kar, S., Banerjee, Russ, J.C., and Fraser,
H.L. Quantification of Microstructural Features in α /β Titanium Alloys.
Materials Science and Engineering A, 2004. 372: p.191-198.
30.Titanium Metals Corporation (Timet). Timetal. Retrieved July 20, 2007
from http://www.timetal.com
31. Lee, Eunha, “Microstructure Evolution and Microstructure/Mechanical
Properties Relationships in α + β Titanium Alloys”, Dissertation, The Ohio
State University, 2004.
32. Gokhale, A. Quantitative Characterization and Representation of Global
Microstructural Geometry. . In ASM Handbook: Volume 9 Metallography
and Microstructure. 2004. Electronic File: ASM International.
33. Russ, J. and Dehoff, R. Practical Stereology. 2003. New York: Plenum
Press.
88
34. Aklemper, J. and Voorhees, P.W. Quantitative Serial Sectioning Analysis.
Journal of Microscopy, 2001. 201: p. 388-394.
35. Chawla, N. and Chawla, K. K. Microstructure-based Modeling of the
Deformation Behavior of Particle Reinforced Metal Matrix Composites.
Journal of Materials Science, 2006. 41: p. 913-925.
36. Basanta, D., Miodownik, M.A., Holm, E. A., and Bentley, P. J. Using
Genetic Algorithms to Evolve Three-Dimensional Microstructures from TwoDimensional Micrographs. Metallurgical and Materials Transactions A,
2005. 36A: p. 1643-1652.
37. Kral, M.V. Three-Dimensional Microscopy. In ASM Handbook: Volume 9
Metallography and Microstructures. 2004. Electronic File: ASM
International.
38. Spowart, J., Mullens, H., and Puchala, P. Collecting and Analylzing
Microstructures in Three Dimensions: A Fully Automated Approach. JOM.
2003. 55: p. 35-37.
39. Spowart, Jonathan E., Automated Serial Sectioning for 3-D Analysis of
Microstructures. Scripta Materialia, 2006. 55: p. 5-10.
40. Wright Patterson Air Force Base. AFRL Transfers Fully Automated 3-D
Microstructure Characterization Technology to Industry. Retrieved
July 25, 2007 from http://www.wpafb.af.mil/news/story.asp?id=123055811
41. Chawla, N., Ganesh, V.V., and Wunsch, B. Three-Dimensional (3D)
Microstructure Visualization and Finite Element Modeling of the Mechanical
Behavior of SiC Particle Reinforced Aluminum Composites. Scripta
Materialia, 2004. 51: p. 161-165.
42. Groeber, M.A., Haley, B.K., Uchic, M.D., Dimiduk, D.M., Ghosh, S. 3D
Reconstruction and Characterization of Polycrystalline Microstructures
Using FIB-SEM System. Materials Characterization, 2006. 57: p. 259-273.
43. Lewis, A.C., Geltmacher, A.B. Image-based Modeling of the Response
of Experimental 3D Microstructures to Mechanical Loading. Scripta
Materialia, 2006. 55: p. 81-85.
44. Dynamic Systems, Inc. Gleeble.com. Retrieved July 25, 2007 from
http://www.gleeble.com.
45. Searles, T. “Microstructural Characterizationof Alpha/beta Titanium Alloy Ti6Al-4V”. Master’s thesis. The Ohio State University, 2005.
89
46. Kremer, J.R., Mastronarde, D.N. and McIntosh, J.R. Computer
Visualization of Three-dimensional Image Data Using IMOD.
Journal of Structural Biology, 1996. 116: p. 71-76.
47. Aaronson, H. I., Spanos, G., Masamukra, R. A., Vardiman, R.G., Moon,
D.W., Menon, E.S.K., et al. Sympathetic Nucleation: An Overview.
Materials Science and Engineering B, 1995. B32: p. 107-123.
90